Add application file

app.py

@@ -1,24 +1,20 @@
 import gradio as gr
-from transformers import AutoFeatureExtractor, AutoModelForImageClassification
+from transformers import AutoImageProcessor, AutoModelForImageClassification
 from PIL import Image
 import torch
 import torch.nn.functional as F
 import pandas as pd
 
-extractor = AutoFeatureExtractor.from_pretrained("nateraw/resnet50-trash-classifier")
-model = AutoModelForImageClassification.from_pretrained("nateraw/resnet50-trash-classifier")
+extractor = AutoImageProcessor.from_pretrained("mrm8488/resnet50-finetuned-trashnet")
+model = AutoModelForImageClassification.from_pretrained("mrm8488/resnet50-finetuned-trashnet")
 
 POUBELLES = {
-    "plastic": "plastique",
+    "cardboard": "papier/carton",
     "glass": "verre",
     "metal": "métal",
     "paper": "papier",
-    "cardboard": "papier/carton",
+    "plastic": "plastique",
     "trash": "ordures ménagères",
-    "compost": "biodéchets",
-    "battery": "déchet dangereux",
-    "clothes": "textile",
-    # Ajoute d'autres si nécessaire
 }
 
 def classify_image(image):
@@ -43,12 +39,10 @@ def classify_image(image):
 
     return pd.DataFrame(rows)
 
-interface = gr.Interface(
+gr.Interface(
     fn=classify_image,
     inputs=gr.Image(type="pil"),
     outputs=gr.Dataframe(),
     title="🗑️ Classifieur de Déchets",
     description="Dépose une image de déchet pour savoir dans quelle poubelle le trier."
-)
-
-interface.launch()
+).launch()